The present invention relates to signal analysis and processing, and more particularly to an improved system and technique for detecting sinusoidal wave signals mixed with ambient noise.
In the field of signal analysis and processing, the ideal method for extracting the signal content from a noisy environment is through the use of a matched filter. However, effective employment of matched filters requires a prior knowledge of both signal frequency and phase which are unknown in most signal detection settings. Accordingly, the traditional method for estimating and extracting the signal content in noise, when the signal frequency is unknown, consists of a spectrum analysis using Fast Fourier Transform (FFT) techniques followed by magnitude detection and incoherent integration. This method, which utilizes amplitude characteristics to analyze and detect signal content, provides processing gains that are significant yet not approaching those obtained by way of matched filters.
Theoretically, it has been determined that by utilizing phase characteristics of incoming signals, increased processing gains approaching those of the matched filters can be obtained. On a practical basis, however, two problems have arisen regarding the utilization of signal phase information in signal detection: first, the signal reference phase must be known a priori, and second, the spectrum analyzer from which the phase information is to be generated limits the detection process because the filter employed therein is generally mismatched as to frequency. While the former problem has been solved through the use of multiple phase references, the latter remains a current problem that restricts signal processing sensitivities and limits signal detection ranges.